Intrusion Detection System Using Ensemble Techinque

Intrusion detection systems, which inspect and analyze network data for signs of hostile activity, are critical to computer network security. These systems are suggested to distinguish and respond to not permitted access, misuse, and other confidence consequences that could concession the concealment, veracity, and accessibility of network resources. In this research, we give an overview of intrusion detection employed in computer networks, including their classification, architecture, and detection methods. The structure intends to detect both recognized-notorious intrusions and attacks with better detection accuracy and lesser untruthful-probability measures. We look at the challenges of setting up and maintaining IDS with their importance in distinguishing various categories of network infringements. This study indicates that intrusion detection systems are an important part of contemporary network protection and are frequently used in many organizations to defend against cyber-attacks. Voting method to identify the intrusion detection systems representing the best performance scores on the dataset. The performance parameter (accuracy, F1_score, precision, and recall) values of the voting model are 0.998015, 0.998015, 0.998016 and 0.998015.